Methods and apparatus for defining an audience for a particular location by surveying nearby receivers and/or passively monitoring content consumption

ABSTRACT

Some embodiments described herein relate to a method that includes surveying and/or passively monitoring content consumption by mobile communication devices. Each signal received from a mobile communication device can be associated with a common location. For example, an out-of-home device positioned at the location can be operable to receive requests from mobile communication devices that represent requests to access network locations. An audience profile for that common location can be defined based on a network location that is identified as being statistically overrepresented. Content targeted to the audience profile at the common location can then be provided.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.15/494,016, filed Apr. 21, 2017, which is a continuation of U.S. patentapplication Ser. No. 15/042,697 (now U.S. Pat. No. 9,635,422), filedFeb. 12, 2016, which claims priority to U.S. Provisional ApplicationSer. No. 62/115,546, entitled “Methods and Apparatus for Defining anAudience for a Particular Location by Surveying Nearby Receivers and/orPassively Monitoring Content Consumption,” filed Feb. 12, 2015, thedisclosure of each of which is hereby incorporated by reference in itsentirety.

BACKGROUND

Some embodiments described herein relate generally to methods andapparatus for defining an audience for a particular location. Forexample, some embodiments described herein relate to an out-of-homedevice surveying nearby receivers and passively monitoring content, suchas programs, channels, websites, etc., consumed by the user of thereceiver.

As computing power and Internet connectivity increases, new roles fordigital devices are constantly emerging. One recent development has beenthe rise in digital out-of-home devices, which can provide dynamicand/or custom content to passersby. For example, building directories,gas-pump information displays, billboards, airplane seat-back displays,taxi information placards and so forth are rapidly being digitizedand/or adding functionalities. At the same time, big data techniques arebeing used to build increasingly sophisticated and granular profiles ofthe general public. To date, however, the ability to develop audienceprofiles for compact public locations, such as the area surrounding anout-of-home device, has been limited. A need therefore exists formethods and apparatus for defining an audience for a particular locationby surveying receivers, such as mobile communication devices, near anout-of-home device and passively monitor content consumed by the userusing the mobile communication device and/or a related computing entity.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a system for dynamically defining anaudience, according to an embodiment.

FIG. 2 is a signal diagram for dynamically defining an audience,according to an embodiment.

FIG. 3. is a representation of scores for an out-of-home device,according to an embodiment.

FIG. 4 illustrates out-of-home devices and their associated scores,according to an embodiment.

DETAILED DESCRIPTION

Content providers have long sought to increase the effectiveness andrelevance of content available to content consumers. In the pre-Internetera, traditional media outlets might target content to an audience basedon crude demographic information. For example, when engaging in atraditional billboard advertising campaign, the advertiser mightconsider the demographics of the neighborhood containing the billboard.Such pre-Internet methods were constrained to relatively imprecisetargeting due to its dependence on relatively unsophisticatedinformation about the audience, such as age, sex, and so forth.

The rise of the Internet has created new opportunities for monitoringmedia consumption and targeting additional content to users based onsuch consumption. Conventionally, content has generally been targetedbased on interests inferred from content consumed by a particular useror a particular device. A need exists for highly-specific location-basedaudience profiles to facilitate unconventional targeting of content canbe targeted based on specific and relatively small locations. In someembodiments described herein out-of-home devices and/or mobilecommunication devices can be treated similar to sensors reportingcontent consumption patterns for a particular location. Thus, alocation-based audience profile can be developed and used to targetcontent to other users associated with that location. In this way, userswho may not otherwise have been identified as having an affinity for aparticular type of content can be targeted based on their presence in alocation linked to that type of content.

Some embodiments described herein relate to out-of-home devices that canbe used to monitor content consumed by users at a particular location.Such content consumption patterns can then be used to define an audienceprofile for that location. In this way, highly granular audienceprofiles can be developed. For example, an out-of-home device can beoperable to detect Wi-Fi signals having a range of approximately 200feet to monitor content consumption patterns for a location. Thus, anaudience profile for an area of approximately 150,000 square feet (e.g.,an area having a radius of approximately 200 feet) can be defined. Then,content can be targeted to that location based on the audience profile.In some instances, such location-based targeted content can be deliveredto users at the location via the out-of-home device. For example, anelectronic billboard at the location can be populated based on theaudience profile, user devices accessing a network location via anetwork access point at the location can be served content based on anidentifier of the network access point, and so forth.

Some embodiments described herein relate to an apparatus that caninclude a device correlation module. The device correlation module canbe implemented in hardware and/or software (e.g. stored on a memoryand/or executing on a processor). The device correlation module can beconfigured to define associations between user devices, such as a mobilecommunication device and a communication device. Such an association canbe defined, for example, based on an indication of network activityassociated with the communication device (e.g., the communication deviceaccessing a webpage, logging into a user account, etc.) and anindication of network activity associated with a mobile communicationdevice. The indication of network activity associated with the mobilecommunication device can be detected by and/or received from anout-of-home device. In some instances, the out-of-home device canprovide network access to the mobile communication device. The apparatuscan also include a traffic analysis module implemented in hardwareand/or software (e.g. stored on a memory and/or executing on aprocessor). The traffic analysis module can be configured to receive anindication of a location associated with the out-of-home device and anetwork log from the out-of-home device. The network log can identifynetwork locations accessed by user devices, (e.g., including the mobilecommunication device). The traffic analysis module can be operable toidentify a network location that is statistically overrepresented in thenetwork log. The apparatus can further include a recommendation module.The recommendation module can be implemented in hardware and/or software(e.g. stored on a memory and/or executing on a processor). Therecommendation module can be operable to define an audience profile forthe location based on the statistically overrepresented networklocation. In some instances, content can be sent to the out-of-homedevice based on the audience profile. Such content can be displayed atthe location (e.g., via the out-of-home device and/or a user device).For example, in an instance where the out-of-home device is or includesan electronic billboard, the electronic billboard can be populated withcontent based on the audience profile for the location. As anotherexample, in an instance where the out-of-home device is or includes anetwork access point, communication devices connected to the out-of-homedevice can be served content based on the audience profile.

Some embodiments described herein relate to a method (optionally acomputer-implemented method) that includes receiving indications ofnetwork activity associated with mobile communication devices. Anindication of a common location for each indication of network activitycan also be received. For example, an out-of-home device can be operableto monitor network activity engaged in by multiple mobile communicationdevices. In addition or alternatively, an indication that a mobilecommunication device accessed a network location can be received fromthat network location, from an Internet service provider (ISP), and/orfrom the mobile communication device itself. An indication of generalnetwork activity, such as Internet traffic data provided by Alexa™ orother analytics provider can be received. The general network activitycan, for example, reflect network activity initiated by a generalpopulation such as users of the Internet at large. Similarly stated, thegeneral network activity may reflect or represent all visits to one ormore network locations and/or may be independent of any particularlocation. A network location that is statistically overrepresented thenetwork activity associated with the mobile communication devicesrelative to the general network activity can be identified. An audienceprofile for a location associated with the out-of-home device can bedefined based on the statistically overrepresented network location.Content can be sent to the out-of-home device, a mobile communicationdevice detected by the out-of-home device, and/or communication devicethat is linked to a mobile communication device detected by theout-of-home device based on the audience profile.

Some embodiments described herein relate to a method (optionally acomputer-implemented method) that includes receiving signalsrepresenting requests to access network locations from mobilecommunication devices. Each signal received from a mobile communicationdevice can be associated with a common location. For example, anout-of-home device positioned at the location can be operable to receiverequests from mobile communication devices that represent requests toaccess network locations. An audience profile for that common locationcan be defined based on a network location that is identified as beingstatistically overrepresented. Content targeted to the audience profileat the common location can then be provided.

FIG. 1 is a schematic diagram of a system 100 for dynamically definingan audience, according to an embodiment. The system 100 includes anout-of-home device 110 and a location correlation server 150. The system100 also includes user devices 140, including a mobile communicationdevice 120 and a communication device 130. A network 190 cancommunicatively couple any device of the system 100 to any other device.The network 190 can be any communication network or combination ofnetworks capable of transmitting information (e.g., data and/or signals)and can include, for example, the Internet, an intranet, a telephonenetwork, an ethernet network, a fiber-optic network, a wireless network,and/or a cellular network.

The mobile communication device 120 can be any suitable computingentity, such as a smart phone, tablet computer, laptop computer, desktopcomputer, etc. The mobile communication device 120 can be a personal-usecomputing device such as a device owned by an individual citizen (e.g.,as distinct from the out-of-home device 110, described in further detailherein, which may be provided by a business to provide content tocustomers of the business and/or bystanders). The mobile communicationdevice 120 can be a receiver for content such as streaming video,Internet activity, broadcast television, etc.

The mobile communication device 120 includes a processor 122 and amemory 124. The processor 122 can be for example, a general purposeprocessor, a Field Programmable Gate Array (FPGA), an ApplicationSpecific Integrated Circuit (ASIC), a Digital Signal Processor (DSP),and/or the like. The processor 122 can be configured to retrieve datafrom and/or write data to memory, e.g., the memory 124, which can be,for example, random access memory (RAM), memory buffers, hard drives,databases, erasable programmable read only memory (EPROMs), electricallyerasable programmable read only memory (EEPROMs), read only memory(ROM), flash memory, hard disks, floppy disks, cloud storage, and/or soforth. The network module 126 can be a wired and/or wirelesstransmission module operable to communicatively couple the mobilecommunication device to the network 190. For example, the network module126 can be a wired and/or wireless network interface controller (NIC), acellular telephone module, a Bluetooth® module, a ZigBee® module,ultrasonic, magnetic and/or any other suitable module configured to sendand/or receive signals via the network 190.

The communication device 130 can be any suitable computing entity, suchas a smart phone, tablet computer, laptop computer, desktop computer,etc. The communication device 130 includes a processor 132, a memory134, and a network module 136, which can be structurally and/orfunctionally similar to the processor 122, the memory 124, and/or thenetwork module 126, respectively, as shown and described above. Asdescribed in further detail herein, the communication device 130 and themobile communication device 120 can be associated with each other andcollectively referred to as user devices 140. In some instances, themobile communication device 120 can be a smart phone and thecommunication device 130 can be a desktop or laptop computer owned by acommon user. In some instances, the mobile communication device 120 mayhave been detected or surveyed by the out-of-home device 110, while thecommunication device 130 may not have been detected or surveyed by theout-of-home device 110. In addition or alternatively, the mobilecommunication device 120 can be operable to report its location to thelocation correlation server 150. In addition or alternatively, thelocation server 150 can ascertain the location of the mobilecommunication device 120 when the mobile communication device 120connects to an ISP, content server, or other suitable device (not shownin FIG. 1) via the network 190.

The out-of-home device 110 can be computing entity having a processor112 and a memory 114, which can be structurally and/or functionallysimilar to the processor 122 and/or the memory 124, respectively,described above. In some embodiments, the out-of-home device 110 canoperable to present custom and/or dynamic content to customers of abusiness and/or bystanders. For example, the out-of-home device 110 canbe a taxi seatback display operable to display driving directions, fareinformation, information about local attractions, product announcements,news, entertainment, etc. As another example, the out-of-home device 110can be an electronic building or shopping center directory, gas pumpdisplay, airline seatback display, electronic billboard, and so forth.As described in further detail herein, the out-of-home device 110 can beconfigured to detect and/or record the presence of nearby mobilecommunication devices (e.g., the mobile communication device 120) andcan present custom and/or dynamic content for the user of the mobilecommunication device 120 and/or can present content based on patterns ofnearby mobile communication devices.

The network module 116 can be operable to survey and/or detect nearbycommunication devices (e.g., communication devices within 50 feet, 100feet, 250 feet, 400 feet, or any other suitable distance). For example,in some embodiments, the out-of-home device 110 can provide a Wi-Fihotspot, and the network module 116 can enable communication devices(e.g., the mobile communication device 120) to connect to theout-of-home device 110. FIG. 1 illustrates the mobile communicationdevice 120 connected to the out-of-home device 110. When a connection isestablished between the mobile communication device 120 and theout-of-home device 110, the mobile communication device 120 can bereferred to as a connected mobile communication device 120.

The out-of-home device 110 can provide connected mobile communicationdevices access to the network 190. Similarly stated, in such anembodiment, when the mobile communication device 120 connects to thenetwork 190 via the out-of-home device 110, the network module 116 cantransfer data from the mobile communication device 120 to the network190 and vice versa. Thus, in such an embodiment, the mobilecommunication device 120 may not be coupled to the network 190 via acellular data link or other connection. The network module 116 can alsobe operable to analyze the traffic requested by the mobile communicationdevice 120 and/or store identifiers associated with the mobilecommunication device 120, such as Media Access Control (MAC) address,user agent, and/or any other suitable information associated withestablishing a WiFi connection and/or embedded in traffic passing to orfrom the connected mobile communication device 120.

In other embodiments, the network module 116 can be a Bluetooth® moduleoperable to “ping” and/or identify nearby communication devices, acellular radio module (e.g., the out-of-home device 110 can be orinclude a micro- or pico-cellular base station), or any other suitablemodule configured to send signals to and/or receive signals from themobile communication device 120 and/or the network 190. The networkmodule 116 can actively request identification information (e.g.,Universally Unique Identifier (UUID), MAC address, etc.) from nearbymobile communication devices and/or may passively monitor (“sniff”) datasent to and/or received from mobile communication device 120 (e.g., whenthe mobile communication device 120 is connected to the network 190 viaa cellular data link or other network access point) to detectidentification information.

The out-of-home device 110 can also include a location module 116, whichcan be a GPS module or any other suitable hardware and/or software(e.g., executing on a processor) module operable to determine thelocation of the out-of-home device 110. For example, in instances wherethe out-of-home device 110 is a mobile device (e.g., a taxi seatbackdisplay) the location module 118 can be operable to monitor the locationof the out-of-home device 110 as the out-of-home device 110 moves. Inother embodiments, for example where the out-of-home device 110 isstationary (e.g. a billboard on a bus shelter), the out-of-home device110 may not include the location module 118. In such an instance, thelocation of the out-of-home device 110 can be stored in the memory 114of the out-of-home device 110 and/or the memory 154 of the locationcorrelation server 150. In some instances, the out-of-home device 110can provide location services, such as mapping information, nearbyrestaurants or other points of interest, and so forth to the audience ofthe out-of-home device and/or the connected mobile communication device120 based on the location determined by the location module 116 and/orstored in the memory 114, 154.

The location correlation server 150 is a computing entity that includesa processor 152, a memory 154, and a network module 156, each of whichmay be structurally and/or functionally similar to the processor 122,the memory 124, and/or the network module 126, respectively, as shownand described above. The location correlation server 150 furtherincludes a traffic analysis module 157, a device correlation module 158,and a recommendation module 159.

The device correlation module 158 can be operable to define associationsbetween communication devices, such as the mobile communication device120 and the communication device 130. The mobile communication device120 and the communication device 130 are collectively referred to asuser devices 140. Similarly stated, the mobile communication device 120and the communication device 130 can be related to each other through auser. For instance, the mobile communication device 120 and thecommunication device 130 can be owned and/or used by a commonindividual, or can be owned and/or used by related individuals (e.g.,spouses, parent and child, friends, coworkers, etc.). In otherinstances, the user devices 140 can be owned and/or used by twoindividuals, who may or may not be aware of each other, based on theusers having similar habits, patterns, demographics, etc. The devicecorrelation module 158 can define an association for the user devices140 using any suitable model or technique. Prior to the devicecorrelation module 158 defining the association for the user devices140, the out-of-home device 110 and/or the location correlation server150 may not have any record or information relating to a relationshipexisting between the mobile communication device 120 and thecommunication device 130.

The traffic analysis module 157 can be operable to detect, survey,monitor, and/or analyze network (e.g., Internet) content of the userdevices 140 and is described in further detail below with reference toFIG. 2. The recommendation module 158 can be operable to provide contentrecommendations for the out-of-home device 110 can is described infurther detail below with reference to FIG. 2.

FIG. 2 is a signal diagram 200 for dynamically defining an audience,according to an embodiment. The signal diagram 200 is described withreference to the out-of-home device 110, the mobile communication device120, and the communication device 130 of FIG. 1. The signal diagram alsoincludes the device correlation module 158, the traffic analysis module157, and the recommendation module 159 of the location correlationserver 150 of FIG. 1.

A connection is established between the mobile communication device 120and the out-of-home device 110. Similarly stated, the mobilecommunication device 120 and/or the out-of-home device 110 can exchangesignals 210 associated with, for example, a WiFi connection, the mobilecommunication device 120 being pinged by a Bluetooth® module of theout-of-home device, or any other suitable connection. The out-of-homedevice 110 can detect the presence of the mobile communication device120 when the connection is established. In some instances, theout-of-home device 110 can receive an identifier associated with themobile communication device 120, such as a MAC address, UUID, and/or soforth. In some instances, such as instances where the out-of-home device110 provides a WiFi hotspot, the mobile communication device 120 canaccess the network 190 (e.g., the Internet) via the out-of-home device110. In such an instance, the out-of-home device can monitor trafficrequests from the mobile communication device 120 and/or monitor contentdelivered to the mobile communication device 120.

The out-of-home device 110 can send a signal 220 including dataassociated with the mobile communication device 120 to the devicecorrelation module 158. Signal 220 can include, for example, one or moreidentifiers associated with the mobile communication device 120, one ormore identifiers associated with the out-of-home device 110, such as aserial number and/or location data (e.g., obtained via the locationmodule 118, etc.) Similarly stated, signal 220 can represent theout-of-home device 110 reporting communication devices (including themobile communication device 120) detected nearby, identifiers associatedwith nearby communication devices, and/or network traffic dataassociated with nearby communication devices.

In other embodiments, the device correlation module 158 can be operableto receive data associated with the mobile communication device directlyfrom the mobile communication device 120, from the mobile communicationdevice's 120 ISP, from a network location requested and/or accessed bythe mobile communication device 120 and/or so forth. Similarly stated,the mobile communication device 120 can report its location and/orcontent it requested and/or accessed directly to the device correlationmodule 158 such that signals 210 and/or 220 are not sent. In addition oralternatively, when the mobile communication device 120 requests and/oraccesses a network location, mobile communication device's 120 ISPand/or a server associated with the network location can report themobile communication device's 120 location and/or content accessed bythe mobile communication device 120. As an illustration, a user of themobile communication device 120 can direct the mobile communicationdevice 120 to access a website via a cellular data link. The websiteand/or the cellular data provider can then send a signal to the devicecorrelation module 158 including the location of the mobilecommunication device 120 and/or an indication of the website.

The communication device 130 can send signal 215 representing thecommunication device 130 accessing a content server 160 (not shown inFIG. 1). The communication device 130 accessing the content server 160can be independent of the out-of-home device 110 establishing aconnection with the mobile communication device 120 (e.g., signal 210),and/or the out-of-home device 110 sending signal 220 representing dataassociated with the mobile communication device 120 to the devicecorrelation module 158. Similarly stated, although signals 210 and 215are shown in FIG. 2 on the same horizontal line (representing the sametime), it should be understood that signals 210 and 215 can occur in anyorder and signal 210 does not depend on and is not triggered by signal215 and vice versa.

The content server 160 can be any suitable network (e.g., Internet)content provider, and can be identifiable, for example, by a universalresource locator (URL) and/or IP address. For example, signal 215 canrepresent a user directing the browser of the communication device 130to fetch content from a website and/or the content server 160 returningthe requested content. In some instances, the content returned by thecontent server 160 can include a tracking cookie or other suitabletraffic monitoring device operable to cause the communication device 130to send signal 225 to the device correlation module 158. Signal 225 caninclude one or more identifiers associated with communication device 130and/or signal 215 (e.g., IP address, cookie data, the URL associatedwith the content server 160, etc.). In other instances, the contentserver 160 can send signal 225 reporting traffic activity to the devicecorrelation module 158 (as represented by the dashed portion of signal225).

The device correlation module 158 can correlate the mobile communicationdevice 120 and the communication device 130 (i.e., the user devices140), at 240. In some instances, correlating the user devices 140 can bedeterministic and can be based on, for example, the user logging into acommon account (e.g., email, social networking, etc.) via the mobilecommunication device 120 and the communication device 130. In someinstances, correlating the user devices 140 can be probabilistic andbased on, for example, common network traffic patterns, common contentconsumption patterns, common IP address usage, common location data,and/or any other suitable behavioral indications.

The device correlation module 158 can be operable to associate anynumber of mobile communication devices with any number of communicationdevices. Similarly stated, the out-of-home device 110 can survey and/ordetect multiple mobile communication devices, each of which can beassociated with another communication device(s). By way of example, iffifty mobile communication devices have been detected near theout-of-home device 110, those fifty mobile communication devices caneach be linked to one of fifty other communication devices. In otherinstances, there may not be a 1:1 match. Similarly stated, in someinstances, no match may be found for some mobile communication devicesand/or some mobile communication devices may be linked to more than onecommunication device.

U.S. patent application Ser. No. 14/572,418, entitled “System, Methods,and Apparatus for Providing Content to Related Compute Devices Based onObfuscated Location Data,” which is incorporated herein by reference inits entirety, describes some methods of correlating devices in greaterdetail.

The device correlation module 158 can send signal 245 to the trafficanalysis module 157. Signal 245 can include data associated with theuser devices 140, such as an indication of the association between themobile communication device 120 and the communication device 130. Signal245 can further include an indication of traffic associated with theuser devices 140. Alternatively, the traffic analysis module 157 canreceive traffic data directly from the mobile communication device 120,the communication device 130, the out-of-home device 110, and or thecontent server 160. The traffic analysis module 157 can analyze trafficat 250. For example, at 250, the traffic analysis module can performstatistical analyses of the content requested and/or received at 215,and/or any content requested and/or received by the mobile communicationdevice 120 (e.g., via the out-of-home device 110).

In some instances, traffic analysis can include identifying content thatis statistically overrepresented based on the location of the mobilecommunication device 120 and/or the out-of-home device 110. Similarlystated, the traffic analysis module 157 can calculate a score forcontent associated with the location of the mobile communication device120 and/or the out-of-home device 110. One example for calculating thescore can be ranking the top URLs for the location of the out-of-homedevice 110. For example, the URLs visited by the user devices 140 andany other devices detected near the out-of-home device (and theirassociated devices) can be ranked based on visitation frequency. In someinstances, this ranking can be normalized using, for example, generalweb traffic data. In this way, websites that are more likely to bevisited by users who have been near the out-of-home device 110 than thegeneral web population can be identified.

In some instances, traffic analysis can be represented as a normalizedprobability score. For example, a probability of a user device that hasbeen linked a location and/or to the out-of-home device 110 (e.g., atlocation X) visiting a particular website (e.g., www.foo.com) (e.g.,within a pre-determined time period, such as a week, a month, a year,etc.) can be calculated based on traffic patterns. For example, in aninstance where fifty mobile communication devices have each been linkedto one of fifty communication devices, and five communication deviceshave visited www.foo.com (e.g., as reported with signal 225), theprobability of a user in the audience of location X (P(foo.com|locationX)) visiting www.foo.com can be 10%. This probability can be normalizedby dividing by the general population's probability of visitingwww.foo.com, which can be expressed as (P|foo.com). The score (S) forfoo.com at location X can be represented as:

$\begin{matrix}{{S\left( {{{foo}.{com}},{{location}\mspace{14mu} X}} \right)} = \frac{P\left( {{foo}.{com}} \middle| {{location}\mspace{14mu} X} \right)}{P\left( {{foo}.{com}} \right)}} & \lbrack 1\rbrack\end{matrix}$

Thus, if two of every one hundred Internet users has visited www.foo.com(e.g., within the pre-determined time period), P(foo.com) can be 2%, andS(foo.com, location X) can be 5, which can represent that the audienceof the out-of-home device 110 is five times more likely to visitwww.foo.com than the general public.

Similarly, a score (S) can be calculated for arbitrary content and/orscores (S) can be calculated for any location. Similarly stated,although S is shown as a function of foo.com and location X, it shouldbe understood that this is for illustrative purposes only and that, forexample, S(bar, location Y) can be calculated based on mobilecommunication devices observed by an out-of-home device at location Yand survey data indicating a probability of a user of the mobilecommunication device to visit www.bar.com, watch the “bar” televisionshow, the “bar” YouTube® channel, the “bar” streaming content, receivethe “bar” magazine, etc.

The traffic analysis module 157 can send signal 255 to therecommendation module 159. Signal 255 can include an indication of highscoring content for the location of the out-of-home device 110. Forexample, signal 255 can include an indication of the URLs moststatistically overrepresented at the location of the out-of-home device110, as compared to, for example, general web traffic.

The recommendation module 159 can define an audience profile, at 260.For example, based on signal 255, the recommendation module 159 candefine demographic and/or contextual profiles for the audience of thelocation associated with the mobile communication device 120 and/or theout-of-home device 110. For example, if content associated with luxuryitems is overrepresented in the traffic analysis, the recommendationmodule 159 can infer that the audience near the out-of-home device 110is wealthier than average. Similarly, if content associated with sportsis overrepresented in the traffic analysis, the recommendation module159 can infer that the audience near the out-of-home device 110 isyounger, and/or more active than average.

The recommendation module 159 can also be operable to correlate audienceprofile to available content and send signal 265 to the out-of-homedevice 110. In some instances, signal 265 can include a recommendationof the website with the highest score, such that the out-of-home device110 requests and/or receives the highest scoring website, at 270, from acontent server 160 hosting that website. In other instances, therecommendation module 159 can recommend content associated with theaudience profile, but not necessarily a high-scoring website. Forexample, if an audience profile indicates a high concentration ofskiers, the recommendation module 159 may determine that the audience ofthe out-of-home device 110 may be interested in snow reports, extremesports programming, skiing product announcements, etc. Signal 265 canrecommend the out-of-home device 110 display such content, and theout-of-home device 110 can request and/or receive such content, at 270,from a content server 160 hosting such content.

In yet other instances, the recommendation module 159 can identifysponsored content based on the audience. For example, because someout-of-home devices 110 offset the cost of operation by displayingsponsored content and/or product announcements, defining audienceprofiles, at 260, for a relatively small location and/or relativelysmall number of users can be an effective way to identify nicheaudiences and/or to provide highly targeted content and productannouncements. As an illustration, if the audience contains aconcentration of skiers, ski equipment retailers and/or manufacturersmay be willing to pay substantial premiums to display announcements forproducts and/or services and/or offers to this concentrated targetmarket as compared to, for example, traditional mass media channels,which are likely to reach a much lower concentration of avid skiers.

In addition or alternatively, the content recommended by therecommendation module 159 can be served to the mobile communicationdevice 120 and/or the communication device 130. For example, in aninstance where the out-of-home device 110 is operable to provide anetwork access point, recommended content can be served to the mobilecommunication device 120 via the out-of-home device 110 when the mobilecommunication device 120 is connected to the out-of-home device 110.Furthermore, the content server 170 can be operable to serve therecommended content to one or both of the user devices 140 via any othersuitable network access point (e.g., other than the out-of-home device110), such as a cellular data link, a home ISP, etc. based on, forexample, an identifier (e.g., a MAC address, UUID, etc.) of the mobilecommunication device 120. For example, the mobile communication device120 can report its identifier to the content server 170 when the mobilecommunication device is connected to the network via a cellular dataconnection (e.g., via a network gateway other than the out-of-homedevice 110). The content server 170 can be operable to recognize thatthe mobile communication device 120 was detected at the locationassociated with the out-of-home device 110 and select and/or provide therecommended content to the mobile communication device 120 based on theaudience profile. Similarly, based on the content server 170 recognizingthat the mobile communication device 120 was detected at the locationassociated with an audience profile indicating an affinity for thecontent, the recommended content can be provided to the communicationdevice 130 based on the mobile communication device 120 being correlatedto the communication device 130.

FIG. 3. is a representation of scores for an out-of-home device 310,according to an embodiment. FIG. 3 illustrates the location of theout-of-home device 310 in Irvine, Calif. The out-of-home device 310 canbe similar to the out-of-home device 110 shown and described above withreference to FIGS. 1 and 2. In this instance, the out-of-home device 310is a digital canvas on a bus shelter. The out-of-home device 310 can beused to present visual and/or audio content, such as entertainmentand/or announcements for products and/or services to individuals whilethey wait for the bus and/or as they walk by. As described above, theout-of-home device 310 can be operable to detect mobile communicationdevices of users near the bus shelter. For example, the out-of-homedevice 310 can offer a WiFi hotspot and/or include a Bluetooth® moduleoperable to survey nearby mobile communication devices. The out-of-homedevice 310 can report nearby mobile communication devices and/orInternet traffic associated with nearby mobile communication devicebrowsing activity to a location correlation server, which can beoperable to link or otherwise associate those mobile communicationdevices with other communication devices used by the same user(s). Inaddition or alternatively, mobile communication devices, ISPs, networklocations, etc. can report Internet traffic and/or location dataassociated with the mobile communication devices. The locationcorrelation server 150 can then be operable to filter mobilecommunication devices 120 that have been reported in a location near thebus stop depicted in FIG. 3 and/or evaluate traffic patterns associatedwith such mobile devices while such mobile devices are located near thelocation depicted in FIG. 3 and/or traffic data that occurs away fromthe location depicted in FIG. 3, but associated with mobilecommunication devices that have been detected near the location depictedin FIG. 3 within an appropriate time period, such as 1 hour, 12 hours, 3days, 1 month, etc.

Furthermore, in some instances some or all mobile communication devices120, such as smart phones detected near the out-of-home device can belinked to one or more communication devices 130, such laptop or desktopcomputer(s). Linking a smart phone to a laptop or desktop computer canprovide additional and/or more meaningful traffic data, because userstypically engage in more and/or different browsing behavior on laptopsand/or desktops than smart phones.

As described above, the location correlation server can analyze thetraffic and calculate scores 350 for content associated with thelocation. The scores 350 are normalized scores indicating URLs that areoverrepresented for the audience of the out-of-home device 310. Forexample, local radio stations and news sources are overrepresented. Alsooverrepresented is swell.com, an online surf shop. This may indicatethat the area surrounding the bus shelter having the out-of-home device310 includes a higher proportion of surfers than the general population.Based on this information, swell.com, surf board makers, swimsuitretailers, and/or other outdoor-focused retailers may have an interestin presenting content and/or product and/or service announcements usingthe out-of-home device 310.

FIG. 4 illustrates out-of-home devices and their associated scores forswell.com in the Southern Los Angeles metro area. Each dot represents anout-of-home device and the normalized score for the nearby audience forswell.com. As described above, a nearby audience can be, for example,the audience within wireless network range of the out-of-home device. Atypical, wireless network range associated with the Institute ofElectrical and Electronics Engineers (IEEE) 802.11 standard isapproximately 200 feet. Thus, a profile for the audience can be linkedto an area of approximately 250,000 square feet. Such highly granularaudience profiles can enable extremely localized targeting of contentbased on interests specific to a very small area. For example, anout-of-home device on a transportation corridor (e.g., street, bus line,train line, etc.) that links a population center to a recreation centersuch as a beach may have a highly localized increased affinity forsurfing. Furthermore, such an affinity may rapidly decrease as thedistance from the transportation corridor grows. Similarly stated, alocation as little as ½ mile, 2 miles, 5 miles, etc. from thetransportation corridor may not have a statistically overrepresentedaffinity for surfing. Although each dot in FIG. 4 represents anout-of-home device, in other instances, each dot may not represent anout-of-home device, but may simply represent a relatively smalllocation, such as an area of approximately 250,000 square feet.

Furthermore, as illustrated in FIG. 4, such highly localized audienceprofiles can enable a large number of audience profiles to be definedwithin a city. Historically, advertisers might target content to anentire city or perhaps a neighborhood, but content consumption basedaudience profiles for small areas relatively closely spaced (e.g.,within V, mile, within 2 miles, etc.) based on content consumptionpatterns was not generally feasible. Out-of-home devices, however, canbe closely spaced, monitor content in a small area, and be used toproduce highly granular audience profiles.

In FIG. 4, the darker dots represent out-of-home devices with localaudiences having a greater affinity for surfing. Out-of-home devicesindicated with a flag have audiences that are six or more times morelikely to have visited swell.com than the general population. A contentprovider interested in providing information to surfers may be motivatedto target these locations. Similarly, an out-of-home device provider maybe able to more effectively offset the cost of providing the device bypartnering with content providers with an interest in niche audiencesoverrepresented in that location.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. For example, some embodiments describe location profilesassociated with an area of approximately 250,000 square feet. It shouldbe understood that any suitable highly-granular location profile may beconstructed. For example, a location profile may be associated with anarea of approximately 50,000 square feet, 100,000 square feet, 500,000square feet, etc.

Where methods described above indicate certain events occurring incertain order, the ordering of certain events may be modified.Additionally, certain of the events may be performed repeatedly,concurrently in a parallel process when possible, as well as performedsequentially as described above. Although various embodiments have beendescribed as having particular features and/or combinations ofcomponents, other embodiments are possible having a combination of anyfeatures and/or components from any of embodiments where appropriate aswell as additional features and/or components.

For example, although some embodiments described herein relate to usingan out-of-home device surveying or detecting mobile communicationdevices and define a profile for the location of the out-of-home device,it should be understood that this is by way of example and notlimitation. In other embodiments, audience profiles for any location canbe defined based on any suitable device detecting any other suitabledevice. For example, in some embodiments, a home or business router candetect and/or survey nearby computing entities. Based on detecting acomputing entity, a location correlation server can associate thedetected computing entity with another computing entity and/or define anaudience profile for the location of the router.

For another example, although some embodiments describe an out-of-homedevice detecting nearby mobile communication devices and defining anaudience profile for the location of the out-of-home device based on thedetected mobile communication devices, in other embodiments, an audienceprofile for any location (e.g., a location without an out-of-homedevice) can be defined based on any suitable data that associatescommunication devices with locations. For example, in some instances,application (app) developers can receive location information for mobilecommunication devices executing their app. An audience profile for anylocation can be defined based on identifying mobile communicationdevices that have been to an identified location, associating mobilecommunication devices that have been to the identified location withcommunication device(s), and/or analyzing the traffic of those mobilecommunication devices and/or associated communication device(s). Thisaudience profile can be used to, for example, provide custom contentand/or product offers to that location via traditional media such asdirect mail, billboards, video screens, etc. or used for any othersuitable purpose. In addition or alternatively, this audience profilecan be used to provide custom content and/or product offers to theidentified location via an out-of-home device that may not be operableto identify nearby mobile communication devices.

For another example, where some embodiments describe analyzing traffic,calculating an audience profile, etc., it should be understood thatthese events can be repeated to, for example update the audience profileover any suitable interval. For instance, an out-of-home device in amountain resort may have a high proportion of golfers during the summerand a high proportion of skiers in the winter season. For anotherexample, an out-of-home device in a downtown neighborhood may have ahigh proportion of business people during the day, and a high proportionof nightclub visitors during the night. The methods described herein canbe operable to identify changing audience profiles by, for example,calculating audience profiles over suitable time scales (e.g., hourly,weekly, monthly, etc.). Furthermore, audience profiles can be combinedacross time periods. For example, an audience profile for Tuesdays canbe calculated by updating a record of mobile communication devicesdetected on one Tuesday with mobile communication devices detected thenext Tuesday. An audience profile for the 5 o'clock hour can similarlybe updated. In this way, the content provided via the out-of-home devicecan be dynamically updated to match the current audience as determinedby detecting and/or making predictions about communication devices thatare currently nearby.

As another example, although audience profiles are described as beingused to select content for out-of-home devices, in other instances,audience profiles collected via out-of-home devices can be used toperform any suitable audience analysis. For example, if the audienceprofile for a location changes (e.g., over a one to two year period) toindicate increased interest in craft beers or independent music, thiscan be indicative that the location is transitioning to a younger and/orhipper neighborhood. Such information can be used to select, forexample, where to locate a business catering to younger populations,such as a boutique scarf shop, where to send traditional bulk mailproduct announcements targeting such an audience, project home valueprices, and so forth.

As another example, although some embodiments describe audience profilesbeing calculated based on traffic patterns of multiple user devicesassociated with multiple users, in other embodiments, a specific usercan be targeted. For example, an out-of-home device can detect aspecific user device. A location correlation server can calculate aprofile for the specific user of that device, and content can beprovided for that one user.

Where methods are described, it should be understood that the methodscan stored as code in a non-transitory computer readable medium. Suchcode can be configured to cause a processor to execute the method and/orcause the processor to bring about an event. Similarly stated, wheremethods are described, it should be understood that the methods can beimplemented by a computer. Some embodiments described herein relate tocomputer-readable medium. A computer-readable medium (orprocessor-readable medium) is non-transitory in the sense that it doesnot include transitory propagating signals per se (e.g., a propagatingelectromagnetic wave carrying information on a transmission medium suchas space or a cable). The media and computer code (also can be referredto as code) may be those designed and constructed for the specificpurpose or purposes including for example some or all of the processesand methods described above. Examples of non-transitorycomputer-readable media include, but are not limited to: magneticstorage media such as hard disks, floppy disks, and magnetic tape;optical storage media such as Compact Disc/Digital Video Discs(CD/DVDs), Compact Disc-Read Only Memories (CD-ROMs), and holographicdevices; magneto-optical storage media such as optical disks; carrierwave signal processing modules; and hardware devices that are speciallyconfigured to store and execute program code, such as ASICs, PLDs, ROMand RAM devices. Other embodiments described herein relate to a computerprogram product, which can include, for example, the instructions and/orcomputer code discussed herein.

Examples of computer code include, but are not limited to, micro-code ormicro-instructions, machine instructions, such as produced by acompiler, code used to produce a web service, and files containinghigher-level instructions that are executed by a computer using aninterpreter. For example, embodiments may be implemented using Java,C++, or other programming languages (e.g., object-oriented programminglanguages) and development tools. Additional examples of computer codeinclude, but are not limited to, control signals, encrypted code, andcompressed code.

What is claimed is:
 1. A non-transitory processor-readable mediumstoring code configured to be executed on a processor, the codecomprising code configured to cause the processor to: receive,indications of network activity associated with a mobile communicationdevice; define an audience profile for a location based, at least inpart on the network activity; and send content to a user at the locationbased, at least in part the audience profile for the location.